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@InProceedings{AndradeFranAlme:2015:DeClPa,
               author = "Andrade, Alexandre Curvelo de and Francisco, Cristiane Nunes and 
                         Almeida, Cl{\'a}udia Maria de",
          affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Desempenho de classificadores param{\'e}trico e n{\~a}o 
                         param{\'e}trico na classifica{\c{c}}{\~a}o da fisionomia 
                         vegetal",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "7611--7618",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The present work is committed to conduct a comparative analysis 
                         between two supervised classifiers, Maximum Likelihood and Support 
                         Vector Machine, respectively parametric and non-parametric, for 
                         the classification of vegetal physiognomies using very high 
                         spatial resolution imagery, emphasizing the gain in performance 
                         with the accordingly increase in the number of attributes. The 
                         database consisted of pan-sharpened QuickBird images and 
                         transformed images derived from the original bands besides relief 
                         data obtained from the TOPODATA Project. The study area extends 
                         over a surface of 16 km2 and is located within the municipality of 
                         Nova Friburgo, in the mountainous region of Rio de Janeiro state. 
                         In total, four experiments were accomplished all of them combining 
                         the adopted classifier with a different number of attributes. In 
                         the first two experiments, only the four QuickBird spectral bands, 
                         previously subject to geometric and radiometric corrections, were 
                         used. In the remainder two experiments, eighteen input bands were 
                         employed. The Kappa indices obtained with the Maximum Likelihood 
                         classifier lied between 0.64 and 0.66, while those obtained for 
                         the Support Vector Machine ranged from 0.52 to 0.80. Considering 
                         the attained results, we concluded that the number of input bands 
                         does not meaningfully increase the accuracy of the Maximum 
                         Likelihood classifier, whereas this factor greatly influences the 
                         Support Vector Machine performance.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "1750",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4K9E",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3JM4K9E",
           targetfile = "p1750.pdf",
                 type = "Processamento de imagens",
        urlaccessdate = "25 jan. 2021"
}


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